3DSpineMFE
A MATLAB® toolbox that given a three-dimensional spine reconstruction computes a set of characteristic morphological measures that unequivocally determine the spine shape.
NeuroR is a collection of tools to repair morphologies.
There are presently three types of repair which are outlined below.
This is the process of sanitizing a morphological file. It currently:
The cut plane repair aims at regrowing part of a morphologies that have been cut out when the cell has been experimentally sliced.
neuror cut-plane repair
contains the collection of CLIs to perform this repair.
Additionally, there are CLIs for the cut plane detection and writing detected cut planes to JSON files:
neuror cut-plane file<br />
neuror cut-plane folder<br />
```<br />
* If the cut plane is not one the X, Y or Z axes, the detection has to be performed through the helper web application that can be launched with the following CLI:<br />
<br />
```<br />
neuror cut-plane hint<br />
```<br />
### Unravelling<br />
Unravelling is the action of “stretching” the cell that has been shrunk because of the dehydratation caused by the slicing.<br />
The unravelling CLI sub-group is:<br />
```<br />
neuror unravel<br />
```<br />
The unravelling algorithm can be described as follows:<br />
* Segments are unravelled iteratively.<br />
<br />
* Each segment direction is replaced by the averaged direction in a sliding window around this segment.<br />
<br />
* The original segment length is preserved.<br />
<br />
* The start position of the new segment is the end of the latest unravelled segment.
A MATLAB® toolbox that given a three-dimensional spine reconstruction computes a set of characteristic morphological measures that unequivocally determine the spine shape.
Arbor is a high-performance library for computational neuroscience simulations with multi-compartment, morphologically-detailed cells, from single cell models to very large networks. Arbor is written from the ground up with many-cpu and gpu architectures in mind, to help neuroscientists effectively use contemporary and future HPC systems to meet their simulation needs. Arbor supports NVIDIA and AMD GPUs as well as explicit vectorization on CPUs from Intel (AVX, AVX2 and AVX512) and ARM (Neon and SVE). When coupled with low memory overheads, this makes Arbor an order of magnitude faster than the most widely-used comparable simulation software. Arbor is open source and openly developed, and we use development practices such as unit testing, continuous integration, and validation.
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